CN111400845B

CN111400845B - Power generation performance evaluation method and device of wind turbine generator

Info

Publication number: CN111400845B
Application number: CN201811612111.2A
Authority: CN
Inventors: 欧发顺; 李强; 赵树椿
Original assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Current assignee: Beijing Goldwind Science and Creation Windpower Equipment Co Ltd
Priority date: 2018-12-27
Filing date: 2018-12-27
Publication date: 2024-05-17
Anticipated expiration: 2038-12-27
Also published as: CN111400845A

Abstract

The invention provides a power generation performance evaluation method and device of a wind turbine, wherein the power generation performance evaluation method comprises the following steps: acquiring wind resource data of the wind turbine generator in a preset time period in real time; carrying out data binning according to the first turbulence intensity in the wind resource data to obtain a first wind speed corresponding to each first turbulence intensity in each turbulence intensity interval; for each turbulence intensity interval, acquiring an actual power curve corresponding to each wind speed interval based on a first power value corresponding to each first wind speed in each wind speed interval; obtaining a design power curve of the wind turbine generator corresponding to each wind speed interval under each turbulence intensity interval; and carrying out power generation performance evaluation on the wind turbine generator based on the actual power curve and the designed power curve. By adopting the power generation performance evaluation method and the power generation performance evaluation device, the influence of external factors such as turbulence intensity on the power generation performance evaluation can be effectively reduced, and the power generation performance evaluation of the wind turbine generator set is more accurate.

Description

Power generation performance evaluation method and device of wind turbine generator

Technical Field

The invention relates to the technical field of wind power generation, in particular to a method and a device for evaluating the power generation performance of a wind turbine.

Background

The power generation performance of the wind turbine generator is one of important indexes for representing the overall performance of the wind turbine generator, and the power curve is a reference index for measuring the power generation performance of the wind turbine generator. The quality of the power curve is directly related to the power generation capacity of the wind turbine, and the power curve of the current wind turbine becomes one of the most important indexes for the owners to check the power generation performance of the wind turbine. In order to evaluate whether the actual output of the wind turbine meets the contract requirements, the power curve needs to be verified.

Currently, verification is generally based on a comparison of a representative power curve and an actual power curve of a wind turbine under ideal operating conditions. However, in actual situations, because the regional range covered by the wind power plant is large, the difference of the terrain conditions between the machine positions is large, so that the working conditions of the wind power plant at each machine position are not completely the same, and are different from the ideal working conditions, the comparison result of the actual power curve and the representative power curve has large errors, and the evaluation of the power generation performance of the wind power plant is inaccurate.

Disclosure of Invention

An object of exemplary embodiments of the present invention is to provide a method and an apparatus for evaluating power generation performance of a wind turbine, so as to overcome at least one of the above drawbacks.

In one general aspect, there is provided a method for evaluating power generation performance of a wind turbine, including: acquiring wind resource data of the wind turbine generator in a preset time period in real time; carrying out data binning according to the first turbulence intensity in the wind resource data to obtain a plurality of turbulence intensity intervals, and obtaining a first wind speed corresponding to each first turbulence intensity in each turbulence intensity interval; for each turbulence intensity interval, carrying out data binning according to all first wind speeds in the turbulence intensity interval to obtain a plurality of wind speed intervals, and respectively obtaining an actual power curve corresponding to each wind speed interval based on first power values corresponding to each first wind speed in each wind speed interval; obtaining a design power curve of the wind turbine generator corresponding to each wind speed interval under each turbulence intensity interval; and carrying out power generation performance evaluation on the wind turbine generator based on the actual power curve and the designed power curve.

Optionally, the power generation performance evaluation method may further include: the method comprises the steps of obtaining first air density corresponding to each first turbulence intensity in each turbulence intensity interval, wherein the step of obtaining an actual power curve corresponding to each wind speed interval comprises the following steps: for each turbulence intensity interval, carrying out data binning on all first air densities in the turbulence intensity interval, obtaining first wind speeds corresponding to the first air densities in each air density interval, and for each air density interval, carrying out data binning on all first wind speeds in the air density interval, obtaining a plurality of wind speed intervals, and respectively obtaining an actual power curve corresponding to each wind speed interval based on first power values corresponding to the first wind speeds in each wind speed interval.

Optionally, a plurality of design power curves corresponding to different wind speed intervals under different air density intervals under different turbulence intensity intervals of the wind turbine generator may be stored in the design power curve library, wherein the design power curve library may be established by: the method comprises the steps of obtaining historical wind resource data of a wind turbine generator, and obtaining a design power curve corresponding to each wind speed interval under each turbulence intensity interval by respectively carrying out data binning according to second turbulence intensity, second air density and second wind speed in the historical wind resource data, wherein the design power curve corresponding to each wind speed interval under each turbulence intensity interval of the wind turbine generator can be obtained from a design power curve library.

Optionally, the wind resource data may include an actual wind speed at a site where the wind turbine is located and an actual power generation value of the wind turbine within the preset time period, where the preset time period includes a plurality of data periods, and the first wind speed of each data period may be an average value of all actual wind speeds within each data period, the first power value of each data period may be an average value of all actual power generation values within each data period, and the first turbulence intensity of each data period may be determined according to a first wind speed and a standard deviation of wind speed of each data period at the site where the wind turbine is located.

Optionally, the wind resource data may include an ambient temperature and an altitude at a site where the wind turbine is located within the preset time period, the preset time period including a plurality of data periods, wherein the first air density of each data period may be determined by: and determining the first air density of each data period according to the altitude of the wind turbine at the site and the average ambient temperature in each data period.

Optionally, the wind resource data may include an atmospheric pressure, an ambient temperature, and a water vapor pressure at a site where the wind turbine is located within the preset time period, the preset time period including a plurality of data periods, wherein the first air density of each data period may be determined by: and determining the first air density of each data period according to the average ambient temperature, the average atmospheric pressure and the average water vapor pressure in each data period at the machine point of the wind turbine generator.

Alternatively, the power generation performance of the wind turbine may be evaluated based on an actual power curve corresponding to any wind speed interval at any air density interval at any turbulence intensity interval and a design power curve corresponding to any wind speed interval at any air density interval at any turbulence intensity interval by: calculating the average value of each first power value in any wind speed interval in any air density interval in any turbulence intensity interval according to the actual power curve as an actual average power value; calculating the average value of each second power value in any wind speed interval in any air density interval in any turbulence intensity interval according to the design power curve as a design average power value; determining a standard wind speed value of any wind speed interval; determining an actual wind frequency distribution value of any wind speed interval; calculating the consistency index of the actual power curve and the designed power curve according to the actual average power value, the designed average power value, the standard wind speed value and the actual wind frequency distribution value; and evaluating the power generation performance of the wind turbine generator set in any wind speed interval in any air density interval in any turbulence intensity interval according to the consistency index.

Optionally, the step of evaluating the generating performance of the wind turbine based on the actual power curve and the designed power curve may further include: acquiring a consistency index corresponding to each actual power curve corresponding to each wind speed interval under each air density interval under each turbulence intensity interval; setting a weight value for each actual power curve; determining the consistency of the total power curve of the wind turbine generator based on the consistency index corresponding to each actual power curve and the corresponding weight value; and evaluating the total power generation performance of the wind turbine according to the consistency of the total power curve.

In another general aspect, there is provided a power generation performance evaluation device of a wind turbine, including: the data acquisition module is used for acquiring wind resource data of the wind turbine generator in a preset time period in real time; the turbulence data binning module is used for carrying out data binning according to first turbulence intensity in the wind resource data to obtain a plurality of turbulence intensity intervals, and obtaining first wind speeds corresponding to first turbulence intensities in each turbulence intensity interval; the actual power curve generation module is used for dividing data into bins according to all first wind speeds in each turbulence intensity interval to obtain a plurality of wind speed intervals, and acquiring an actual power curve corresponding to each wind speed interval based on first power values corresponding to each first wind speed in each wind speed interval respectively; the design power curve acquisition module is used for acquiring a design power curve corresponding to each wind speed interval of the wind turbine generator set under each turbulence intensity interval; and the power generation performance evaluation module is used for evaluating the power generation performance of the wind turbine generator set based on the actual power curve and the design power curve.

Optionally, the turbulence data binning module may further obtain a first air density corresponding to each first turbulence intensity in each turbulence intensity interval, where the power generation performance evaluation device may further include: the density data binning module is used for carrying out data binning on all first air densities in each turbulence intensity interval to obtain a plurality of air density intervals, and obtaining first wind speeds corresponding to the first air densities in each air density interval, wherein the actual power curve generating module can be used for carrying out data binning on all first wind speeds in each air density interval to obtain a plurality of wind speed intervals according to each air density interval, and obtaining an actual power curve corresponding to each wind speed interval based on first power values corresponding to each first wind speed in each wind speed interval.

Optionally, a plurality of design power curves corresponding to different wind speed intervals under different air density intervals under different turbulence intensity intervals of the wind turbine generator may be stored in the design power curve library, where the power generation performance evaluation device may further include a design power curve library building module, and the design power curve library is built by: the method comprises the steps of obtaining historical wind resource data of a wind turbine generator, and obtaining a design power curve corresponding to each wind speed interval under each turbulence intensity interval by respectively carrying out data binning according to second turbulence intensity, second air density and second wind speed in the historical wind resource data, wherein the design power curve obtaining module can obtain the design power curve corresponding to each wind speed interval under each turbulence intensity interval of the wind turbine generator from a design power curve library.

Optionally, the wind resource data may include an actual wind speed at a site where the wind turbine is located and an actual power generation value of the wind turbine within the preset time period, where the preset time period includes a plurality of data periods, the data acquisition module may determine an average value of all the actual wind speeds within each data period as a first wind speed of each data period, the data acquisition module may determine an average value of all the actual power generation values within each data period as a first power value of each data period, and the data acquisition module may determine a first turbulence intensity of each data period according to a first wind speed and a standard deviation of a wind speed of each data period at the site where the wind turbine is located.

Optionally, the wind resource data may include an ambient temperature and an altitude at a location of the wind turbine within the preset time period, and the preset time period includes a plurality of data periods, where the data acquisition module may determine the first air density of each data period according to the altitude at the location of the wind turbine and an average ambient temperature within each data period.

Optionally, the wind resource data may include an atmospheric pressure, an ambient temperature and a water vapor pressure at a location of the wind turbine at the preset time period, and the preset time period includes a plurality of data periods, wherein the data acquisition module may determine the first air density of each data period according to an average ambient temperature, an average atmospheric pressure and an average water vapor pressure in each data period at the location of the wind turbine.

Optionally, the power generation performance evaluation module may evaluate the power generation performance of the wind turbine generator based on an actual power curve corresponding to any wind speed interval under any air density interval under any turbulence intensity interval and a design power curve corresponding to the any wind speed interval under any air density interval under any turbulence intensity interval by: calculating the average value of each first power value in any wind speed interval in any air density interval in any turbulence intensity interval according to the actual power curve as an actual average power value; calculating the average value of each second power value in any wind speed interval in any air density interval in any turbulence intensity interval according to the design power curve as a design average power value; determining a standard wind speed value of any wind speed interval; determining an actual wind frequency distribution value of any wind speed interval; calculating the consistency index of the actual power curve and the designed power curve according to the actual average power value, the designed average power value, the standard wind speed value and the actual wind frequency distribution value; and evaluating the power generation performance of the wind turbine generator set in any wind speed interval in any air density interval in any turbulence intensity interval according to the consistency index.

Alternatively, the power generation performance evaluation module may include: the index obtaining sub-module is used for obtaining a consistency index corresponding to each actual power curve corresponding to each wind speed interval under each air density interval under each turbulence intensity interval; the weight setting sub-module is used for setting a weight value for each actual power curve; the total index determining submodule is used for determining the total power curve consistency of the wind turbine generator based on the consistency index corresponding to each actual power curve and the corresponding weight value; and the total power generation performance evaluation sub-module evaluates the total power generation performance of the wind turbine generator set according to the consistency of the total power curve.

In another general aspect, there is provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of evaluating power generation performance of a wind turbine as described above.

In another general aspect, there is provided a computing device, the computing device comprising: a processor; and the memory is used for storing a computer program, and when the computer program is executed by the processor, the power generation performance evaluation method of the wind turbine generator set is realized.

By adopting the method and the device for evaluating the power generation performance of the wind turbine generator, disclosed by the embodiment of the invention, the influence of external factors such as turbulence intensity on the power generation performance evaluation can be effectively reduced, so that the power generation performance evaluation of the wind turbine generator is more accurate.

Drawings

The foregoing and other objects and features of the invention will become more apparent from the following description taken in conjunction with the accompanying drawings in which:

FIG. 1 illustrates a flow chart of a method of power generation performance assessment of a wind turbine according to an exemplary embodiment of the invention;

FIG. 2 illustrates a flow chart of a method of power generation performance evaluation of a wind turbine according to another exemplary embodiment of the invention;

FIG. 3 shows a flowchart of steps for power generation performance evaluation of a wind turbine in accordance with an exemplary embodiment of the present invention;

FIG. 4 illustrates a block diagram of a power generation performance evaluation apparatus of a wind turbine according to an exemplary embodiment of the present invention;

fig. 5 shows a block diagram of a power generation performance evaluation module according to an exemplary embodiment of the present invention.

Detailed Description

Various example embodiments will now be described more fully with reference to the accompanying drawings, in which some example embodiments are shown.

FIG. 1 is a flowchart of a method of power generation performance assessment of a wind turbine according to an exemplary embodiment of the invention.

Referring to fig. 1, in step S10, wind resource data of a wind turbine generator in a preset time period is acquired in real time. Here, the preset time period may refer to a duration of an evaluation period during which the wind turbine generator is evaluated for power generation performance. The preset time period may include a plurality of data periods, and the first turbulence intensity, the first wind speed, and the first power value of the plurality of data periods may be determined according to the acquired wind resource data, respectively.

Preferably, the wind resource data may be wind resource data at a site of the wind turbine, in which case the determined first turbulence intensity and first wind speed may be turbulence intensity and wind speed at the site of the wind turbine for a preset period of time.

For example, wind resource data at each machine location in a wind farm can be obtained by using at least one wind tower arranged in the wind farm, respectively, and then by simulation. However, the present invention is not limited thereto, and wind resource data at a site where the wind turbine is located may be obtained by installing various sensors on the wind turbine, for example, wind speed may be measured by an anemometer provided on the wind turbine, or ambient temperature may be sensed by a temperature sensor provided on the wind turbine, etc., which is not exemplified herein.

For example, the wind resource data of the wind turbine may be collected with a predetermined sampling period (e.g., 1 second) and the first turbulence intensity, the first wind speed and the first power value may be calculated every 10 minutes with a predetermined period (e.g., 10 minutes) as one data period. Here, the power generation performance of the wind turbine generator may be evaluated as long as the data amount of the first turbulence intensity, the first wind speed and the first power value determined based on the collected wind resource data of the wind turbine generator can support the subsequent data binning processing. Taking the case that the data period is 10 minutes as an example, 3 months can be taken as an evaluation period, so that the duration of the current assessment period (the current case is usually taken as an assessment period of one year) is greatly shortened, and timely discovery of the problematic wind turbine generator is facilitated.

It should be understood that the specific values listed above are only examples, but the present invention is not limited thereto, and those skilled in the art can adjust the duration of the predetermined sampling period, the duration of the data period, and the duration of the evaluation period according to actual needs.

For example, the wind resource data may include an actual wind speed at a location of the wind turbine and an actual power generation value of the wind turbine over a preset period of time.

In this case, the first wind speed for each data period may be an average of all actual wind speeds within each data period. The first power value for each data cycle may be an average of all actual power generation values within each data cycle.

The first turbulence intensity for each data cycle may be determined from a first wind speed and a standard deviation of wind speed for each data cycle at a site of the wind turbine.

For example, the first turbulence intensity for any data period may be calculated using the following formula:

In the formula (1), TI is the first turbulence intensity of any data period, sigma is the standard deviation of wind speed in any data period, Is the average of the actual wind speeds for any one data period (i.e., the first wind speed).

Preferably, the power generation performance evaluation method of a wind turbine according to an exemplary embodiment of the present invention may further include: and cleaning the wind resource data of the wind turbine generator in a preset time period.

For example, the acquired wind resource data of the wind turbine generator can be cleaned according to IEC61400-12-1 standard so as to remove the data which does not meet the standard requirements. As an example, data outside the following ranges may be eliminated from the wind resource data to determine a first turbulence intensity, a first wind speed, and a first power value from the cleaned wind resource data: wind speed range of 0 m/s-50 m/s, -peak staggering angle range of 90-90 degrees, generator rotating speed range of 0-2000 revolutions per minute (rpm), pitch angle range of 10-95 degrees, -environment temperature range of 50-50 degrees, and actual power value range of 0-1.5 times rated power.

In step S20, data binning is performed according to the first turbulence intensity in the wind resource data, so as to obtain a plurality of turbulence intensity intervals, and a first wind speed corresponding to each first turbulence intensity in each turbulence intensity interval is obtained.

Here, the magnitude of the turbulence intensity has a larger influence on the output of the wind turbine, which is generally shown that the larger the turbulence intensity is in a low wind speed section, the higher the power value output by the wind turbine is, and in a power curve transition stage (which means that the impeller rotation speed has reached the rated rotation speed, but the power value output by the wind turbine has not reached the rated power wind speed section), the larger the turbulence intensity is, and the lower the power value output by the wind turbine is.

In the exemplary embodiment of the invention, based on the influence of the turbulence intensity on the power value of the wind turbine, data binning is performed on all the first turbulence intensities of a plurality of data periods to obtain a plurality of turbulence intensity intervals, so that the finally obtained actual power curve corresponds to each turbulence intensity interval, and thus, the influence of the turbulence intensity on the power generation performance evaluation of the wind turbine can be effectively reduced, and the evaluation result is more accurate.

It should be appreciated that a person skilled in the art may determine the value range of the turbulence intensity interval according to actual needs, for example, the value range of the turbulence intensity interval may be divided into smaller values for more accurate evaluation of the power generation situation of the wind turbine generator.

In step S30, for each turbulence intensity interval, data is divided into bins according to all the first wind speeds in the turbulence intensity interval, so as to obtain a plurality of wind speed intervals, and an actual power curve corresponding to each wind speed interval is obtained based on the first power value corresponding to each first wind speed in each wind speed interval.

As an example, the first wind speed data binning and power calculation may be performed according to the IEC61400-12-1 specification, the result of the calculation being wind speed and power relations corresponding to each wind speed interval at different turbulence intensity intervals, i.e. the actual power curve.

For example, for any turbulence intensity interval, all the first wind speeds in the any turbulence intensity interval can be subjected to data binning to obtain a plurality of wind speed intervals, then for each wind speed interval, a first power value corresponding to each first wind speed in the wind speed interval is obtained, and then an actual power curve corresponding to the wind speed interval is obtained according to the first power value corresponding to each first wind speed.

Here, the actual power curve corresponding to the wind speed interval may be obtained according to the first power value corresponding to each first wind speed by various methods, which is not limited in the present invention.

In step S40, a design power curve corresponding to each wind speed interval of the wind turbine generator and each turbulence intensity interval is obtained.

For example, a plurality of design power curves corresponding to different wind speed intervals at different turbulence intensity intervals of the wind turbine may be stored in the design power curve library. In this case, a design power curve corresponding to each wind speed interval in each obtained turbulence intensity interval of the wind turbine generator may be obtained from a design power curve library.

Here, the design power curve library may be established based on historical wind resource data of the wind turbine generator, and it should be understood that, to ensure accuracy of the power generation performance evaluation result, a manner of obtaining a plurality of design power curves in the design power curve library should be the same as a manner of obtaining an actual power curve according to wind resource data of the wind turbine generator within a preset time period. That is, the manner of processing the historical wind resource data of the wind turbine generator to generate the designed power curve should be the same as the manner of processing the wind resource data of the wind turbine generator in the preset time period to generate the actual power curve. For example, when the two power curves are obtained, the data of turbulence intensity and wind speed should be divided into bins in the same way, the duration of the data period should be the same, and the duration of the predetermined sampling period for collecting wind resource data should be the same.

Preferably, the library of design power curves can be established by: and acquiring historical wind resource data of the wind turbine generator, and acquiring a design power curve corresponding to each wind speed interval under each turbulence intensity interval by respectively carrying out data binning according to the second turbulence intensity and the second wind speed in the acquired historical wind resource data.

Here, the second turbulence intensity, the second wind speed and the second power value of the predetermined number of data periods may be determined according to the acquired historical wind resource data, and the second turbulence intensity and the second wind speed may be data binned according to the same data binning processing manner as the wind resource data in the predetermined period.

For example, all second turbulence intensities are data binned to obtain a plurality of turbulence intensity intervals. Here, the number of the plurality of turbulence intensity sections obtained by data binning all the second turbulence intensities and the value range of each turbulence intensity section are the same as the number of the plurality of turbulence intensity sections obtained by data binning all the first turbulence intensities and the value range of each turbulence intensity section.

In this case, for each turbulence intensity interval, all the second wind speeds within that turbulence intensity interval are data binned to obtain a plurality of wind speed intervals. Here, the number of the plurality of wind speed sections and the value range of each wind speed section obtained by data binning all the second wind speeds are the same as the number of the plurality of wind speed sections and the value range of each wind speed section obtained by data binning all the first wind speeds. After the second wind speeds are subjected to data binning, a design power curve corresponding to each wind speed interval is obtained based on the second power values corresponding to the second wind speeds in each wind speed interval.

In step S50, the wind turbine generator is subjected to power generation performance evaluation based on the actual power curve and the designed power curve.

For example, after obtaining a plurality of actual power curves and corresponding design power curves corresponding to respective wind speed sections at each turbulence intensity section through the above-described steps, the power generation performance of the wind turbine generator at any wind speed section at any turbulence intensity section may be evaluated based on the actual power curve (hereinafter referred to as a first predetermined actual power curve) and the corresponding design power curve (hereinafter referred to as a first predetermined design power curve) corresponding to any wind speed section at any turbulence intensity section. After all the power generation performances of the wind turbine generator set in each wind speed interval in each turbulence intensity interval are evaluated, the total power generation performance of the wind turbine generator set can be determined.

Preferably, the wind turbine generator may be evaluated for generating performance based on a first predetermined actual power curve corresponding to any wind speed interval at any turbulence intensity interval and a first predetermined design power curve corresponding to said any wind speed interval at said any turbulence intensity interval in the following manner.

And calculating the average value of each first power value in any wind speed interval under any turbulence intensity interval according to a first preset actual power curve as an actual average power value. And calculating the average value of each second power value in any wind speed interval under any turbulence intensity interval according to the first preset design power curve as a design average power value. And determining a standard wind speed value of any wind speed interval. And determining the actual wind frequency distribution value of any wind speed interval. And calculating the consistency index of the first preset actual power curve and the first preset design power curve according to the actual average power value, the design average power value, the standard wind speed value and the actual wind frequency distribution value. And evaluating the power generation performance of the wind turbine generator set in any wind speed interval in any turbulence intensity interval according to the consistency index.

For example, when the consistency index is greater than or equal to the set point, it is determined that the first predetermined actual power curve meets the requirements for the compliance of the first predetermined design power curve, and when the consistency index is less than the set point, it is determined that the first predetermined actual power curve does not meet the requirements for the compliance of the first predetermined design power curve.

It should be understood that the above power generation performance evaluation method is only a preferred example, and the present invention is not limited thereto, and those skilled in the art may also evaluate the power generation performance of the wind turbine generator in other manners. For example, the annual average wind frequency distribution (which can be obtained through wind tower data) can be used for combining an actual power curve and a designed power curve, calculating a converted actual annual energy generation amount and a theoretical energy generation amount, calculating a ratio of the actual annual energy generation amount to the theoretical energy generation amount, determining that the coincidence degree of the actual power curve and the designed power curve meets the requirement when the ratio is larger than or equal to a set proportion value, and determining that the coincidence degree of the actual power curve and the designed power curve does not meet the requirement when the ratio is smaller than the set proportion value.

Here, in the method for evaluating the power generation performance of the wind turbine shown in fig. 1, the influence of turbulence intensity on the power generation performance evaluation of the wind turbine is considered, in the actual power generation process, the difference of external wind resource conditions can cause the wind turbine to have a difference in power generation performance, and according to the analysis of the operation data of the wind turbine, it is found that besides the turbulence intensity, the influence of the air density on the power generation performance of the wind turbine is also larger, that is, the magnitude of the air density can influence the power generation performance evaluation result of the wind turbine.

As an example, the effect of air density on the power value output by a wind turbine may be represented by the following formula:

In the formula (2), P represents the power value output by the wind turbine generator, C _p represents the wind energy utilization coefficient, ρ represents the air density, A represents the impeller wind sweeping area, and V represents the wind speed.

In another exemplary embodiment of the invention, the influence of turbulence intensity and air density on the power generation performance evaluation of the wind turbine is considered, so that the power generation performance evaluation of the wind turbine is more accurate. The process of evaluating the power generation performance of a wind turbine based on turbulence intensity and air density is described below with reference to fig. 2.

Fig. 2 shows a flowchart of a method of evaluating the power generation performance of a wind turbine according to another exemplary embodiment of the invention.

Referring to fig. 2, in step S100, wind resource data of a wind turbine generator in a preset time period is acquired in real time. Here, the preset time period may refer to a duration of an evaluation period during which the wind turbine generator is evaluated for power generation performance. The preset time period may include a plurality of data periods, and the first turbulence intensity, the first air density, the first wind speed, and the first power value of the plurality of data periods may be determined according to the acquired wind resource data, respectively.

Preferably, the obtained wind resource data may be wind resource data at a site where the wind turbine is located, in which case the determined first turbulence intensity, first air density, first wind speed are turbulence intensity, air density and wind speed at the site where the wind turbine is located within a preset period of time.

Here, the manner of determining the first turbulence intensity, the first wind speed and the first power value in step S100 is the same as the manner of determining the first turbulence intensity, the first wind speed and the first power value in step S10 of fig. 1, and the disclosure of this part will not be repeated.

The manner in which the first air density of the plurality of data periods is determined from the wind resource data at the site of the wind turbine is described below.

In one example, the first air density may be determined based on an ambient temperature and a altitude of the sea.

In this case, the wind resource data may include an ambient temperature and an altitude at a site where the wind turbine is located within a preset period of time.

The first air density for each data cycle may be determined by: and determining the first air density of each data period according to the altitude of the wind turbine at the site and the average ambient temperature in each data period.

For example, the first air density for any data period may be calculated using the following formula:

In the formula (3), ρ ₁ is the first air density of any data period, T is the average ambient temperature of any data period, and H is the altitude of the site where the wind turbine generator is located.

In another example, the first air density may be determined from atmospheric pressure, ambient temperature, and water vapor pressure.

In this case, the wind resource data may include atmospheric pressure, ambient temperature, and water vapor pressure at the site of the wind turbine for a preset period of time.

The first air density for each data cycle may be determined by: and determining the first air density of each data period according to the average ambient temperature, the average atmospheric pressure and the average water vapor pressure in each data period at the machine point of the wind turbine generator.

For example, by means of a anemometer tower in a wind farm, barometers and thermometers may be installed, typically in the anemometer tower, for measuring barometric data (e.g. barometric pressure and water vapour pressure) and ambient temperature. Preferably, according to the air pressure data and the environmental temperature obtained by the wind measuring tower, the air pressure data and the environmental temperature at the position of the wind turbine generator can be calculated.

As an example, the first air density for any data period may be calculated using the following formula:

In formula (4), ρ ₁ is the first air density of any data period, T is the average ambient temperature of any data period, P _A is the average atmospheric pressure of any data period, and e is the average water vapor pressure of any data period.

In step S200, data binning is performed according to the first turbulence intensity in the acquired wind resource data, so as to obtain a plurality of turbulence intensity intervals, and a first air density corresponding to each first turbulence intensity in each turbulence intensity interval is acquired.

In step S300, for each turbulence intensity interval, data are binned according to all the first air densities in the turbulence intensity interval, so as to obtain a plurality of air density intervals, and a first wind speed corresponding to each first air density in each air density interval is obtained.

In step S400, for each air density interval, data is divided into bins according to all the first wind speeds in the air density interval, so as to obtain a plurality of wind speed intervals, and an actual power curve corresponding to each wind speed interval is obtained based on the first power value corresponding to each first wind speed in each wind speed interval.

For example, for any air density interval, all the first wind speeds in the any air density interval can be subjected to data binning to obtain a plurality of wind speed intervals, then for each wind speed interval, a first power value corresponding to each first wind speed in the wind speed interval is obtained, and then an actual power curve corresponding to the wind speed interval is obtained according to the first power value corresponding to each first wind speed.

In step S500, a design power curve corresponding to each wind speed interval of the wind turbine generator and each air density interval of each turbulence intensity interval is obtained.

For example, a plurality of design power curves corresponding to different wind speed intervals in different air density intervals in different turbulence intensity intervals of the wind turbine generator are stored in a design power curve library. In this case, a design power curve corresponding to each wind speed interval in each air density interval in each turbulence intensity interval of the wind turbine generator may be obtained from the design power curve library.

Here, a design power curve library may be established based on historical wind resource data of the wind turbine, and a manner of obtaining a plurality of design power curves in the design power curve library is the same as a manner of obtaining an actual power curve according to wind resource data of the wind turbine in a preset time period. For example, when the two power curves are obtained, the data binning modes of turbulence intensity, air density and wind speed should be the same, the duration of the data period should be the same, and the duration of the predetermined sampling period for collecting wind resource data should be the same.

Preferably, the library of design power curves can be established by: and acquiring historical wind resource data of the wind turbine generator, and acquiring a design power curve corresponding to each wind speed interval under each turbulence intensity interval by respectively carrying out data binning according to the second turbulence intensity, the second air density and the second wind speed in the acquired historical wind resource data.

Here, the second turbulence intensity, the second air density, the second wind speed and the second power value of the predetermined number of data periods may be determined according to the acquired historical wind resource data, and the data binning may be performed on the second turbulence intensity, the second air density and the second wind speed according to the same data binning processing manner as the wind resource data in the predetermined period.

In this case, for each turbulence intensity interval, all the second air densities within that turbulence intensity interval are data binned to obtain a plurality of air density intervals. Here, the number of the plurality of air density sections obtained by data binning all the second air densities and the value range of each air density section are the same as the number of the plurality of air density sections obtained by data binning all the first air densities and the value range of each air density section.

And carrying out data binning on all second wind speeds in each air density interval to obtain a plurality of wind speed intervals. Here, the number of the plurality of wind speed sections and the value range of each wind speed section obtained by data binning all the second wind speeds are the same as the number of the plurality of wind speed sections and the value range of each wind speed section obtained by data binning all the first wind speeds. After the second wind speeds are subjected to data binning, a design power curve corresponding to each wind speed interval is obtained based on the second power values corresponding to the second wind speeds in each wind speed interval.

In step S600, the wind turbine generator is subjected to power generation performance evaluation based on the actual power curve and the designed power curve.

As an example, the power generation performance of the wind turbine may be evaluated based on a degree of coincidence between the actual power curve and the designed power curve (i.e., power curve coincidence degree CAPC, conformity Analysis of Power Curve).

For example, after obtaining a plurality of actual power curves and corresponding design power curves corresponding to respective wind speed sections at each air density section at each turbulence intensity section through the above steps, the power generation performance of the wind turbine generator at any wind speed section at any air density section at any turbulence intensity section can be evaluated based on the actual power curve (hereinafter referred to as a second predetermined actual power curve) and the corresponding design power curve (hereinafter referred to as a second predetermined design power curve) corresponding to any wind speed section at any air density section at any turbulence intensity section. After all the power generation performance of the wind turbine generator in each wind speed interval in each air density interval in each turbulence intensity interval is evaluated, the total power generation performance of the wind turbine generator can be determined.

A process of evaluating the power generation performance of the wind turbine generator based on the second predetermined actual power curve corresponding to any wind speed section in any air density section in any turbulence intensity section and the second predetermined design power curve corresponding to any wind speed section in any air density section in any turbulence intensity section will be described below with reference to fig. 3.

FIG. 3 shows a flowchart of steps for power generation performance evaluation of a wind turbine in accordance with an exemplary embodiment of the present invention.

Referring to fig. 3, in step S501, an average value of each first power value in any wind speed section in any air density section in any turbulence intensity section is calculated as an actual average power value according to a second predetermined actual power curve.

In step S502, an average value of each second power value in any wind speed section in any air density section in any turbulence intensity section is calculated as a design average power value according to a second predetermined design power curve.

In step S503, a standard wind speed value for any wind speed section is determined. As an example, the standard wind speed value may refer to a wind speed value of the arbitrary wind speed section specified in the IEC specification.

In step S504, an actual wind frequency distribution value for any wind speed section is determined. As an example, the actual wind frequency distribution value may refer to a ratio of a duration of the actual wind speed within the arbitrary wind speed interval to a total duration of the preset time period within the preset time period.

In step S505, a consistency index of the second predetermined actual power curve and the second predetermined design power curve is calculated according to the actual average power value, the design average power value, the standard wind speed value, and the actual wind frequency distribution value.

As an example, a consistency index between an actual power curve corresponding to an air density ρ _a, a turbulence intensity TI _b, and a designed power curve corresponding to an air density ρ _a, a turbulence intensity TI _b may be calculated using the following index tool:

In the formula (5), CAPC (ρ _a,TI_b) represents a consistency index between an actual power curve and a designed power curve corresponding to the air density ρ _a and the turbulence intensity TI _b, P (ρ _a,TI_b,v_i) represents an actual average power value of the wind turbine at the ith wind speed interval under the condition that the air density ρ _a is the turbulence intensity TI _b, P ₀(ρ_a,TI_b,v_i) represents a designed average power value of the wind turbine at the ith wind speed interval under the condition that the air density ρ _a is the turbulence intensity TI _b, v _i represents a standard wind speed value of the ith wind speed interval, and α _i represents an actual wind frequency distribution value of the ith wind speed interval. Here, ρ _a may represent a representative air density value for any air density interval, and TI _b may represent a representative turbulence intensity value for any turbulence intensity interval.

It should be appreciated that the manner in which the compliance index is calculated shown in fig. 5 is merely an example, and that other manners of determining compliance of the actual power curve with the design power curve are possible.

In step S506, the power generation performance of the wind turbine generator set under any wind speed interval condition under any air density interval under any turbulence intensity interval is evaluated according to the consistency index.

For example, when the consistency index is greater than or equal to the set value, determining that the consistency between the second predetermined actual power curve and the second predetermined design power curve meets the requirement, that is, the power generation performance of the wind turbine generator set in any wind speed interval in any air density interval in any turbulence intensity interval can be considered to meet the requirement.

When the consistency index is smaller than the set value, determining that the consistency of the second preset actual power curve and the second preset design power curve does not meet the requirement, namely, considering that the power generation performance of the wind turbine generator set in any wind speed interval in any air density interval in any turbulence intensity interval does not meet the requirement.

It should be appreciated that the steps shown in fig. 3 may be utilized to evaluate the power generation performance of the wind turbine generator based on the actual power curve and the designed power curve corresponding to each wind speed interval at each air density interval at each turbulence intensity interval, so as to determine the power generation performance of the wind turbine generator under different wind speed interval conditions at different air density intervals at different turbulence intensity intervals. And obtaining the total power generation performance evaluation result of the wind turbine based on the determined power generation performance.

It should be understood that the power generation performance evaluation manner shown in fig. 3 is only a preferred example, and the present invention is not limited thereto, and those skilled in the art may also evaluate the power generation performance of the wind turbine generator in other manners. For example, the annual average wind frequency distribution, the actual power generation amount and the theoretical power generation amount can be calculated according to the annual average wind frequency distribution and by combining the actual power curve and the designed power curve, the ratio of the actual annual power generation amount to the theoretical power generation amount is calculated, and the consistency between the actual power curve and the designed power curve is determined according to the calculated ratio.

The process of determining the overall power generation performance evaluation result of the wind turbine generator is described below.

For example, a consistency index corresponding to each actual power curve corresponding to each air speed interval under each turbulence intensity interval is obtained, a weight value is set for each actual power curve, the consistency of the total power curve of the wind turbine is determined based on the consistency index corresponding to each actual power curve and the corresponding weight value, and the total power generation performance of the wind turbine is evaluated according to the consistency of the total power curve.

For example, for each actual power curve corresponding to each wind speed interval corresponding to each air density interval under each turbulence intensity interval, the product of the consistency index of the actual power curve and the corresponding design power curve and the corresponding weight is calculated, the consistency of the actual power curve is obtained, the sum of the consistency of all the actual power curves is determined as the total power curve consistency index of the wind turbine, and the total power curve consistency of the wind turbine is determined based on the total power curve consistency index, so that the power generation performance of the wind turbine can be evaluated.

It should be understood that the sum of the weight values corresponding to each actual power curve may be 1, and those skilled in the art may determine the magnitude of each weight value according to the actual needs. Here, setting the weight value for each actual power curve can be understood as setting the weight value for the consistency index corresponding to each actual power curve. As an example, the range of values of each weight value may be greater than zero and less than 1.

For example, the power generation performance evaluation method of a wind turbine according to an exemplary embodiment of the present invention may further include: and sorting the power generation performance of all the wind turbines based on the consistency of the total power curve of each wind turbine in the wind power plant, namely, if the total power curve consistency index of the wind turbines is higher, the power generation performance of the wind turbines is indicated to be better, the sorting is more forward, otherwise, if the total power curve consistency index of the wind turbines is lower, the power generation performance of the wind turbines is indicated to be worse, and the sorting is more backward. Through the sequencing, the wind turbine generator system with poor power generation performance can be rapidly positioned, so that rapid identification and further measures are conveniently taken for investigation and analysis.

In addition, the power generation performance evaluation method of the wind turbine generator set provided by the invention can be embedded into a big data platform (for example, a global monitoring system), so that the wind turbine generator set with poor power generation performance can be rapidly positioned from a large number of wind turbine generator sets, and early warning and further investigation and analysis of the cause of the problem can be given in advance.

Fig. 4 shows a block diagram of a power generation performance evaluation apparatus of a wind turbine according to an exemplary embodiment of the present invention.

As shown in fig. 4, a power generation performance evaluation apparatus of a wind turbine according to an exemplary embodiment of the present invention includes: the system comprises a data acquisition module 10, a turbulence data binning module 20, an actual power curve generation module 30, a design power curve acquisition module 40 and a power generation performance evaluation module 50.

Specifically, the data acquisition module 10 acquires wind resource data of the wind turbine generator in real time within a preset time period. Here, the preset time period may refer to a duration of an evaluation period during which the wind turbine generator is evaluated for power generation performance. The preset time period may include a plurality of data periods, and the data acquisition module 10 may determine the first turbulence intensity, the first wind speed, and the first power value of the plurality of data periods according to the acquired wind resource data, respectively.

Preferably, the wind resource data may be wind resource data at a site where the wind turbine is located, in which case the first turbulence intensity and the first wind speed determined by the data acquisition module 10 may be turbulence intensity and wind speed at the site where the wind turbine is located within a preset period of time.

In this case, the data acquisition module 10 may determine an average of all actual wind speeds over each data period as the first wind speed for each data period. The data acquisition module 10 may determine an average of all actual power generation values within each data period as the first power value for each data period.

The data acquisition module 10 may determine a first turbulence intensity for each data cycle based on a first wind speed and a wind speed standard deviation for each data cycle at a site where the wind turbine is located.

Preferably, the data acquisition module 10 may further perform data cleaning on wind resource data of the wind turbine generator within a preset time period, and determine the first turbulence intensity, the first wind speed and the first power value of the plurality of data periods according to the cleaned wind resource data.

The turbulence data binning module 20 performs data binning according to the first turbulence intensity in the wind resource data to obtain a plurality of turbulence intensity intervals, and obtains a first wind speed corresponding to each first turbulence intensity in each turbulence intensity interval.

The actual power curve generating module 30 performs data binning according to all the first wind speeds in each turbulence intensity interval for each turbulence intensity interval to obtain a plurality of wind speed intervals, and obtains an actual power curve corresponding to each wind speed interval based on the first power value corresponding to each first wind speed in each wind speed interval.

The design power curve acquisition module 40 acquires a design power curve of the wind turbine generator corresponding to each wind speed interval under each turbulence intensity interval.

The power generation performance evaluation module 50 evaluates the power generation performance of the wind turbine generator based on the actual power curve and the design power curve.

It should be appreciated that the above is to consider the influence of turbulence intensity on the power generation performance evaluation of the wind turbine, but in actual production, the influence of air density on the power generation performance of the wind turbine is found to be obvious, for example, the power generation capability of the wind turbine may be obviously different under the high temperature condition or the cold condition in summer, so in a preferred embodiment, the influence of turbulence intensity and air density on the power generation performance of the wind turbine are considered simultaneously when evaluating the power generation performance of the wind turbine.

In this case, the data acquisition module 10 may further determine the first air density of the plurality of data periods according to wind resource data of the wind turbine generator within the preset time period.

In one example, the data acquisition module 10 may determine the first air density based on the ambient temperature and the altitude.

The data acquisition module 10 may determine a first air density for each data cycle based on an altitude at a site where the wind turbine is located and an average ambient temperature within each data cycle.

In another example, the data acquisition module 10 may determine the first air density based on the barometric pressure, the ambient temperature, and the vapor pressure.

The data acquisition module 10 may determine the first air density for each data cycle based on an average ambient temperature, an average barometric pressure, and an average water vapor pressure for each data cycle at the site of the wind turbine.

The turbulence data binning module 20 performs data binning according to the first turbulence intensity in the acquired wind resource data to obtain a plurality of turbulence intensity intervals, and acquires a first air density corresponding to each first turbulence intensity in each turbulence intensity interval.

For the above case where the influence of the air density on the power generation performance of the wind turbine is considered, the power generation performance evaluation device of the wind turbine according to the exemplary embodiment of the present invention may further include: the density data binning module 60 performs data binning according to all the first air densities in each turbulence intensity interval to obtain a plurality of air density intervals, and obtains a first wind speed corresponding to each first air density in each air density interval.

In this case, the actual power curve generating module 30 may perform data binning according to all the first wind speeds in the air density interval for each air density interval, to obtain a plurality of wind speed intervals, and obtain an actual power curve corresponding to each wind speed interval based on the first power values corresponding to the respective first wind speeds in each wind speed interval.

The design power curve obtaining module 40 may obtain a design power curve corresponding to each wind speed interval of the wind turbine generator and each air density interval of each turbulence intensity interval.

For example, a plurality of design power curves corresponding to different wind speed intervals in different air density intervals in different turbulence intensity intervals of the wind turbine generator are stored in a design power curve library.

In this case, the power generation performance evaluation device of a wind turbine according to an exemplary embodiment of the present invention may further include: the design power curve library establishing module 70 is configured to establish a design power curve library, and at this time, the design power curve obtaining module 40 may obtain a design power curve corresponding to each wind speed interval of each turbulence intensity interval of the wind turbine from the design power curve library.

The design power curve library creation module 70 may create a design power curve library by: and acquiring historical wind resource data of the wind turbine generator, and acquiring a design power curve corresponding to each wind speed interval under each turbulence intensity interval by respectively carrying out data binning according to the second turbulence intensity, the second air density and the second wind speed in the acquired historical wind resource data.

Here, the design power curve library creation module 70 may determine the second turbulence intensity, the second air density, the second wind speed, and the second power value for the predetermined number of data periods, respectively, according to the acquired historical wind resource data, and perform data binning on the second turbulence intensity, the second air density, and the second wind speed in the same data binning processing manner as the wind resource data for the predetermined period of time.

As an example, the power generation performance evaluation module 50 may evaluate the power generation performance of the wind turbine based on the consistency compliance between the actual power curve and the design power curve.

For example, the power generation performance evaluation module 50 may evaluate the power generation performance of the wind turbine generator based on an actual power curve corresponding to any wind speed interval at any air density interval at any turbulence intensity interval and a design power curve corresponding to any wind speed interval at any air density interval at any turbulence intensity interval.

According to the actual power curve, calculating the average value of each first power value in any wind speed interval in any air density interval in any turbulence intensity interval as an actual average power value, calculating the average value of each second power value in any wind speed interval in any air density interval in any turbulence intensity interval as a designed average power value according to the designed power curve, determining the standard wind speed value of any wind speed interval, determining the actual wind frequency distribution value of any wind speed interval, calculating the consistency index of the actual power curve and the designed power curve according to the actual average power value, the designed average power value, the standard wind speed value and the actual wind frequency distribution value, and evaluating the power generation performance of the wind turbine generator in any wind speed interval in any turbulence intensity interval according to the consistency index.

After the power generation performance of the wind turbine generator is evaluated based on the actual power curve and the designed power curve corresponding to each wind speed interval under each air density interval under each turbulence intensity interval in the above manner, and the power generation performance of the wind turbine generator under different wind speed intervals under different air density intervals of different turbulence intensity intervals is determined, the total power generation performance evaluation result of the wind turbine generator can be further determined. The process of evaluating the overall power generation performance of a wind turbine will be described with reference to fig. 5.

Fig. 5 shows a block diagram of the power generation performance evaluation module 50 according to an exemplary embodiment of the present invention.

As shown in fig. 5, the power generation performance evaluation module 50 according to an exemplary embodiment of the present invention may include: an index acquisition sub-module 501, a weight setting sub-module 502, a total index determination sub-module 503, and a total power generation performance evaluation sub-module 504.

Specifically, the index acquisition sub-module 501 acquires a consistency index corresponding to each actual power curve corresponding to each wind speed interval at each air density interval at each turbulence intensity interval.

The weight setting sub-module 502 sets a weight value for each actual power curve.

The total index determination submodule 503 determines the total power curve consistency of the wind turbine generator based on the consistency index corresponding to each actual power curve and the corresponding weight value.

The total power generation performance evaluation submodule 504 evaluates the total power generation performance of the wind turbine generator set according to the consistency of the total power curve.

In a preferred embodiment, the power generation performance evaluation module 50 may further rank the power generation performance of all the wind turbines based on the consistency of the total power curve of each wind turbine in the wind farm, so as to quickly locate the wind turbine with poor power generation performance based on the ranking result, so as to facilitate quick identification and further measures for investigation and analysis.

There is also provided, in accordance with an exemplary embodiment of the present invention, a computing device. The computing device includes a processor and a memory. The memory is used for storing a computer program. The computer program is executed by the processor to cause the processor to execute the above-described method for evaluating the power generation performance of a wind turbine.

There is also provided, in accordance with an exemplary embodiment of the present invention, a computer-readable storage medium storing a computer program. The computer readable storage medium stores a computer program that, when executed by a processor, causes the processor to execute the power generation performance evaluation method of a wind turbine set described above. The computer readable recording medium is any data storage device that can store data which can be read out by a computer system. Examples of the computer-readable recording medium include: read-only memory, random access memory, compact disc read-only, magnetic tape, floppy disk, optical data storage device, and carrier waves (such as data transmission through the internet via wired or wireless transmission paths).

By adopting the method and the device for evaluating the power generation performance of the wind turbine generator, disclosed by the embodiment of the invention, the influence of external factors such as turbulence intensity, air density and the like on the power curve conformity is effectively reduced, and the evaluation result on the power generation performance of the wind turbine generator is more accurate.

In addition, by adopting the power generation performance evaluation method and the power generation performance evaluation device for the wind turbine according to the exemplary embodiment of the invention, the actual power curve of the wind turbine is calculated by carrying out data binning on the air density and the turbulence intensity, so that the error caused by the fact that the wind speed is required to be converted through the air density in the conventional evaluation method is reduced, the final result is more accurate, and meanwhile, the influence of different turbulence intensities and different air densities on the actual power output of the wind turbine is fully considered.

In addition, with the power generation performance evaluation method and apparatus of the wind turbine generator according to the exemplary embodiments of the present invention, an algorithm for calculating the consistency index of the actual power curve and the design power curve (i.e., an index tool for defining the consistency of the actual power curve and the design power curve) is defined, by which the power curve consistency calculation can be performed very conveniently.

In addition, by adopting the method and the device for evaluating the power generation performance of the wind turbine generator according to the exemplary embodiment of the invention, the time required for calculating the conformity of the power curve is shortened, and the wind turbine generator can be evaluated for multiple times of power generation performance in one year according to wind conditions in general so as to evaluate the consistency of the power curve of the wind turbine generator under different running conditions.

In addition, by adopting the method and the device for evaluating the power generation performance of the wind turbine generator according to the exemplary embodiment of the invention, the consistency of the actual power curve and the designed power curve can be evaluated more finely, the wind turbine generator with poor power generation performance can be positioned rapidly by ranking the power curve consistency indexes of all the wind turbine generators in the wind power plant, the reason of the poor power generation performance of the wind turbine generator is analyzed in a key way, and corresponding optimization work is performed.

In addition, the method and the device for evaluating the power generation performance of the wind turbine generator set can be used for wind power plants or large data platforms, and can expand the application range of the method or the device, and facilitate early warning or taking further measures for investigation if the method or the device is embedded into a global monitoring system.

While the invention has been shown and described with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made to these embodiments without departing from the spirit and scope of the invention as defined by the following claims.

Claims

1. The power generation performance evaluation method of the wind turbine generator is characterized by comprising the following steps of:

Acquiring wind resource data of the wind turbine generator in a preset time period in real time;

Carrying out data binning according to the first turbulence intensity in the wind resource data to obtain a plurality of turbulence intensity intervals, and obtaining a first wind speed corresponding to each first turbulence intensity in each turbulence intensity interval;

For each turbulence intensity interval, carrying out data binning according to all first wind speeds in the turbulence intensity interval to obtain a plurality of wind speed intervals, and respectively obtaining an actual power curve corresponding to each wind speed interval based on first power values corresponding to each first wind speed in each wind speed interval;

Obtaining a design power curve corresponding to each wind speed interval of the wind turbine generator under each turbulence intensity interval from a design power curve library, wherein the design power curve library is established based on historical wind resource data of the wind turbine generator, and the mode of obtaining a plurality of design power curves in the design power curve library is the same as the mode of obtaining an actual power curve;

And carrying out power generation performance evaluation on the wind turbine generator based on the actual power curve and the design power curve, wherein the power generation performance of the wind turbine generator is evaluated based on the consistency coincidence degree between the actual power curve and the design power curve.

2. The power generation performance evaluation method according to claim 1, further comprising: obtaining first air density corresponding to each first turbulence intensity in each turbulence intensity interval,

Wherein the step of obtaining an actual power curve corresponding to each wind speed interval comprises:

for each turbulence intensity interval, carrying out data binning on all the first air densities in the turbulence intensity interval to obtain a plurality of air density intervals, obtaining first wind speeds corresponding to the first air densities in each air density interval,

For each air density interval, carrying out data binning on all first wind speeds in the air density interval to obtain a plurality of wind speed intervals, and respectively obtaining an actual power curve corresponding to each wind speed interval based on first power values corresponding to the first wind speeds in each wind speed interval.

3. The method for evaluating the power generation performance according to claim 2, wherein a plurality of design power curves corresponding to different wind speed intervals in different air density intervals in different turbulence intensity intervals are stored in the design power curve library,

Wherein, the design power curve library is established by the following modes:

obtaining historical wind resource data of the wind turbine,

By respectively carrying out data binning according to the second turbulence intensity, the second air density and the second wind speed in the historical wind resource data, obtaining a design power curve corresponding to each wind speed interval under each air density interval under each turbulence intensity interval,

And obtaining a design power curve corresponding to each wind speed interval of the wind turbine generator set under each turbulence intensity interval from the design power curve library.

4. The power generation performance evaluation method according to claim 1, wherein the wind resource data includes an actual wind speed at a site where the wind turbine is located and an actual power generation value of the wind turbine within the preset time period, the preset time period includes a plurality of data periods,

Wherein the first wind speed of each data period is an average of all actual wind speeds in each data period,

The first power value of each data cycle is an average value of all actual power generation power values in each data cycle,

The first turbulence intensity of each data period is determined according to the first wind speed and the wind speed standard deviation of each data period at the site of the wind turbine generator.

5. The power generation performance evaluation method according to claim 2, wherein the wind resource data includes an ambient temperature and an altitude at a site where the wind turbine is located within the preset time period, the preset time period includes a plurality of data periods,

Wherein the first air density of each data cycle is determined by:

and determining the first air density of each data period according to the altitude of the wind turbine at the site and the average ambient temperature in each data period.

6. The power generation performance evaluation method according to claim 2, wherein the wind resource data includes an atmospheric pressure, an ambient temperature, and a water vapor pressure at a site where the wind turbine is located during the preset time period, the preset time period including a plurality of data periods,

Wherein the first air density of each data cycle is determined by:

and determining the first air density of each data period according to the average ambient temperature, the average atmospheric pressure and the average water vapor pressure in each data period at the machine point of the wind turbine generator.

7. The power generation performance evaluation method according to claim 2, wherein the power generation performance evaluation of the wind turbine generator is performed based on an actual power curve corresponding to any wind speed section at any air density section at any turbulence intensity section and a design power curve corresponding to the any wind speed section at any air density section at any turbulence intensity section by:

Calculating the average value of each first power value in any wind speed interval in any air density interval in any turbulence intensity interval according to the actual power curve as an actual average power value;

Calculating the average value of each second power value in any wind speed interval in any air density interval in any turbulence intensity interval according to the design power curve as a design average power value;

determining a standard wind speed value of any wind speed interval;

Determining an actual wind frequency distribution value of any wind speed interval;

And calculating the consistency index of the actual power curve and the design power curve according to the actual average power value, the design average power value, the standard wind speed value and the actual wind frequency distribution value.

8. The power generation performance evaluation method according to claim 7, wherein the step of evaluating the power generation performance of the wind turbine based on the actual power curve and the designed power curve further comprises:

acquiring a consistency index corresponding to each actual power curve corresponding to each wind speed interval under each air density interval under each turbulence intensity interval;

setting a weight value for each actual power curve;

Determining the consistency of the total power curve of the wind turbine generator based on the consistency index corresponding to each actual power curve and the corresponding weight value;

and evaluating the total power generation performance of the wind turbine according to the consistency of the total power curve.

9. The utility model provides a generating performance evaluation device of wind turbine generator system which characterized in that includes:

The data acquisition module is used for acquiring wind resource data of the wind turbine generator in a preset time period in real time;

The turbulence data binning module is used for carrying out data binning according to first turbulence intensity in the wind resource data to obtain a plurality of turbulence intensity intervals, and obtaining first wind speeds corresponding to first turbulence intensities in each turbulence intensity interval;

The actual power curve generation module is used for dividing data into bins according to all first wind speeds in each turbulence intensity interval to obtain a plurality of wind speed intervals, and acquiring an actual power curve corresponding to each wind speed interval based on first power values corresponding to each first wind speed in each wind speed interval respectively;

The system comprises a design power curve acquisition module, a wind turbine generator system and a wind speed control module, wherein the design power curve acquisition module acquires a design power curve corresponding to each wind speed interval under each turbulence intensity interval from a design power curve library, the design power curve library is established based on historical wind resource data of the wind turbine generator system, and the mode of acquiring a plurality of design power curves in the design power curve library is the same as the mode of acquiring an actual power curve;

The power generation performance evaluation module is used for evaluating the power generation performance of the wind turbine generator based on the actual power curve and the design power curve, wherein the power generation performance of the wind turbine generator is evaluated based on the consistency coincidence degree between the actual power curve and the design power curve.

10. The power generation performance evaluation device of claim 9, wherein the data acquisition module further acquires a first air density corresponding to each first turbulence intensity within each turbulence intensity interval,

Wherein the power generation performance evaluation device further includes: a density data binning module for data binning all the first air densities in each turbulence intensity interval to obtain a plurality of air density intervals and obtain a first wind speed corresponding to each first air density in each air density interval,

The actual power curve generation module carries out data binning on all first wind speeds in each air density interval to obtain a plurality of wind speed intervals, and obtains an actual power curve corresponding to each wind speed interval based on first power values corresponding to the first wind speeds in each wind speed interval.

11. The power generation performance evaluation device according to claim 10, wherein a plurality of design power curves corresponding to different wind speed intervals at different air density intervals at different turbulence intensity intervals are stored in the design power curve library,

The power generation performance evaluation device further comprises a design power curve library building module, and the design power curve library is built through the following modes:

obtaining historical wind resource data of the wind turbine,

The design power curve acquisition module acquires a design power curve corresponding to each wind speed interval of the wind turbine generator set and each air density interval under each turbulence intensity interval from the design power curve library.

12. The power generation performance evaluation device of claim 9, wherein the wind resource data includes an actual wind speed at a site where the wind turbine is located and an actual power generation value of the wind turbine within the preset time period, the preset time period includes a plurality of data periods,

Wherein the data acquisition module determines an average of all actual wind speeds over each data period as a first wind speed for each data period,

The data acquisition module determines an average value of all actual power generation values in each data period as a first power value for each data period,

The data acquisition module determines a first turbulence intensity of each data period according to a first wind speed and a wind speed standard deviation of each data period at a machine position of the wind turbine generator.

13. The power generation performance evaluation device of claim 10, wherein the wind resource data comprises an ambient temperature and an altitude at a site where the wind turbine is located within the preset time period, the preset time period comprising a plurality of data periods,

The data acquisition module determines a first air density of each data period according to the altitude of the machine point where the wind turbine generator is located and the average ambient temperature in each data period.

14. The power generation performance evaluation device of claim 10, wherein the wind resource data includes atmospheric pressure, ambient temperature, and water vapor pressure at a site where the wind turbine is located for the preset time period, the preset time period including a plurality of data periods,

The data acquisition module determines a first air density of each data period according to average ambient temperature, average atmospheric pressure and average water vapor pressure in each data period at a machine point where the wind turbine generator is located.

15. The power generation performance evaluation device of claim 10, wherein the power generation performance evaluation module evaluates the power generation performance of the wind turbine based on an actual power curve corresponding to any wind speed interval at any air density interval at any turbulence intensity interval and a design power curve corresponding to any wind speed interval at any air density interval at any turbulence intensity interval by:

determining a standard wind speed value of any wind speed interval;

16. The power generation performance evaluation device according to claim 15, wherein the power generation performance evaluation module includes:

the index obtaining sub-module is used for obtaining a consistency index corresponding to each actual power curve corresponding to each wind speed interval under each air density interval under each turbulence intensity interval;

the weight setting sub-module is used for setting a weight value for each actual power curve;

The total index determining submodule is used for determining the total power curve consistency of the wind turbine generator based on the consistency index corresponding to each actual power curve and the corresponding weight value;

and the total power generation performance evaluation sub-module evaluates the total power generation performance of the wind turbine generator set according to the consistency of the total power curve.

17. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements a method of evaluating the generation performance of a wind turbine according to any one of claims 1 to 8.

18. A computing device, the computing device comprising:

A processor;

A memory storing a computer program which, when executed by a processor, implements a method of evaluating the power generation performance of a wind turbine as claimed in any one of claims 1 to 8.